Literature DB >> 32493782

Development and Application of a Core Genome Multilocus Sequence Typing Scheme for the Health Care-Associated Pathogen Pseudomonas aeruginosa.

Richard A Stanton1, Gillian McAllister2, Jonathan B Daniels2, Erin Breaker2, Nicholas Vlachos2, Paige Gable2, Heather Moulton-Meissner2, Alison Laufer Halpin2,3.   

Abstract

Pseudomonas aeruginosa is an opportunistic human pathogen that frequently causes health care-associated infections (HAIs). Due to its metabolic diversity and ability to form biofilms, this Gram-negative nonfermenting bacterium can persist in the health care environment, which can lead to prolonged HAI outbreaks. We describe the creation of a core genome multilocus sequence typing (cgMLST) scheme to provide a stable platform for the rapid comparison of P. aeruginosa isolates using whole-genome sequencing (WGS) data. We used a diverse set of 58 complete P. aeruginosa genomes to curate a set of 4,440 core genes found in each isolate, representing ∼64% of the average genome size. We then expanded the alleles for each gene using 1,991 contig-level genome sequences. The scheme was used to analyze genomes from four historical HAI outbreaks to compare the phylogenies generated using cgMLST to those of other means (traditional MLST, pulsed-field gel electrophoresis [PFGE], and single-nucleotide variant [SNV] analysis). The cgMLST scheme provides sufficient resolution for analyzing individual outbreaks, as well as the stability for comparisons across a variety of isolates encountered in surveillance studies, making it a valuable tool for the rapid analysis of P. aeruginosa genomes. This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.

Entities:  

Keywords:  HAI; Pseudomonas aeruginosazzm321990; antibiotic resistance; cgMLST

Mesh:

Year:  2020        PMID: 32493782      PMCID: PMC7448633          DOI: 10.1128/JCM.00214-20

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   5.948


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